Fine-Tuning LLMs With Retrieval Augmented Generation (RAG)

This approach is a novel implementation of RAG called RA-DIT (Retrieval Augmented Dual Instruction Tuning) where the RAG dataset (query, context retrieved and response) is used to to fine-tune a LLM…

Retrieval-Augmented Generation: How to Use Your Data to Guide LLMs

A Gentle Introduction to Retrieval Augmented Generation (RAG)

Bruno Vicente on LinkedIn: Customer: Garsa

List: General ML & AI, Curated by Fabio Lazzarini

Fine-Tuning LLMs With Retrieval Augmented Generation (RAG), by Cobus Greyling

Prompt Engineering: Retrieval Augmented Generation(RAG), by A B Vijay Kumar

Retrieval Augmented Generation (RAG) in Large Language Model(LLMs)

Retrieval-augmented language models // RALMs, by sbagency

List: RAG, Curated by ShAI Bernard Lelchuk

Retrieval-Augmented Generation (RAG) vs LLM Fine-Tuning, by Cobus Greyling

RAG — Retrieval Augmented Generation, by Cobus Greyling

Knowledge Zone Topic Explorer

RAG vs Finetuning — Which Is the Best Tool to Boost Your LLM Application?, by Heiko Hotz

Freshen up LLMs 'Retrieval Augmented Generation' - The New Stack

Prompt Engineering, RAG, and Fine-tuning: Benefits and When to Use